The Real-Time Mobile Application for Classifying of Endangered Parrot Species Using the CNN Models Based on Transfer Learning
المؤلفون المشاركون
Choe, Daegyu
Choi, Eunjeong
Kim, Dong Keun
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-03-09
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Among the many deep learning methods, the convolutional neural network (CNN) model has an excellent performance in image recognition.
Research on identifying and classifying image datasets using CNN is ongoing.
Animal species recognition and classification with CNN is expected to be helpful for various applications.
However, sophisticated feature recognition is essential to classify quasi-species with similar features, such as the quasi-species of parrots that have a high color similarity.
The purpose of this study is to develop a vision-based mobile application to classify endangered parrot species using an advanced CNN model based on transfer learning (some parrots have quite similar colors and shapes).
We acquired the images in two ways: collecting them directly from the Seoul Grand Park Zoo and crawling them using the Google search.
Subsequently, we have built advanced CNN models with transfer learning and trained them using the data.
Next, we converted one of the fully trained models into a file for execution on mobile devices and created the Android package files.
The accuracy was measured for each of the eight CNN models.
The overall accuracy for the camera of the mobile device was 94.125%.
For certain species, the accuracy of recognition was 100%, with the required time of only 455 ms.
Our approach helps to recognize the species in real time using the camera of the mobile device.
Applications will be helpful for the prevention of smuggling of endangered species in the customs clearance area.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Choe, Daegyu& Choi, Eunjeong& Kim, Dong Keun. 2020. The Real-Time Mobile Application for Classifying of Endangered Parrot Species Using the CNN Models Based on Transfer Learning. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1192328
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Choe, Daegyu…[et al.]. The Real-Time Mobile Application for Classifying of Endangered Parrot Species Using the CNN Models Based on Transfer Learning. Mobile Information Systems No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1192328
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Choe, Daegyu& Choi, Eunjeong& Kim, Dong Keun. The Real-Time Mobile Application for Classifying of Endangered Parrot Species Using the CNN Models Based on Transfer Learning. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1192328
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1192328
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر